Practical Applications of Chlorophyll Fluorescence Measurements

Dear Colleagues,

Currently, chlorophyll fluorescence measurement is regarded as one of the most promising tools in environmental, biological, agricultural, and horticultural sciences. The objective of this Special Issue of Plants is to gather impactful papers that are related to the practical application of chlorophyll fluorescence measurement across various domains, including plant sciences, ecosystem monitoring, industrial applications, and the commercial and civil sectors.

This technique’s utility in non-invasively monitoring the health and stress responses of plants makes it invaluable in sustainable agriculture practices and precision farming. By assessing how plants absorb light and convert it to energy, chlorophyll fluorescence can reveal much about a plant’s physiological state under different environmental conditions.

Further integration of chlorophyll fluorescence with Artificial Intelligence (AI) and Machine Learning (ML) technologies opens new avenues for advancements. AI and ML can enhance the interpretation of fluorescence data, providing more accurate assessments of plant health, predicting future growth patterns, and optimizing conditions for plant resilience. Moreover, the combination of chlorophyll fluorescence measurement with AI and ML can facilitate the creation of biological feedback systems that enable plants to control their growth environments.

Potential papers may cover, but are not limited to, the following topics:

• The development of AI models that integrate chlorophyll fluorescence data to track plant health and productivity.
• Machine Learning algorithms for predicting plant physiological status, diseases, and pests based on fluorescence signals.
• The use of drone and satellite imaging to measure chlorophyll fluorescence at a large scale for ecosystem monitoring or agricultural management.
• Case studies on the use of chlorophyll fluorescence in agriculture and horticulture to improve plant breeding and reduce costs and waste.
• Innovative approaches in hardware and software for enhancing the sensitivity and accuracy of chlorophyll fluorescence measurements.

This Special Issue aims to showcase research that exemplifies the intersection of chlorophyll fluorescence with cutting-edge computational technologies, highlighting the technique’s potential to revolutionize fields from bio-monitoring to commercial agriculture. Contributions that demonstrate novel applications, particularly those that bridge traditional scientific boundaries, are especially welcomed.

Dr. Piotr Dabrowski
Prof. Dr. Hazem M. Kalaji
Guest Editors

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• abiotic and biotic stresses
• agricultural management
• artificial intelligence (AI)
• biological feedback systems
• chlorophyll fluorescence measurement
• ecosystem monitoring
• machine learning (ML)
• plant health
• precision farming
• sustainable agriculture
• technological integration